The evaluation of stocks and other financial investments is a complex issue. A number of methods and strategies to rank stocks have been developed but they suffer from a number of limitations. For example, most stock ranking models in the prior art focus on a single approach—being typically growth or value oriented—without taking into accounts all factors that drive a stock's attractiveness. The purpose of many models is to help investors in the selection of stocks and the construction of portfolios that theoretically outperform the market, but in doing so they introduce a bias into the investment strategy and allow little adaptation to the personal investment strategy of the investor.
The universe of stocks considered by prior art methods is generally quite limited and usually covering only one country and/or few indices thus reducing their effectiveness. When stocks are ranked, they are often ranked against each other within a fixed universe with little consideration given to the investment universe of the investor. There is little focus given to the comparison of the relative attractiveness of industry peers and, when done, they suffer from the lack of accurate peer groups. Furthermore, stock scores or ranks used in the prior art are often described by a set of numbers which are difficult and time-consuming to interpret. Some prior art methods summarize stocks visually using use a star-based rating which oversimplifies the analysis.
There is a desire for a system and method for evaluating financial investments that overcomes the limitations of the prior art.